Treemaps for Directed Acyclic Graphs. - Vassilis Tsiaras; Sofia Triantafilou; Ioannis G. Tollis (GD, 2007)

Visualization of Proofs in Defeasible Logic. - Ioannis Avguleas; Katerina Gkirtzou; Sofia Triantafilou; Antonis Bikakis; Grigoris Antoniou; Efstratios Kontopoulos; Nick Bassiliades (RuleML, 2008)

DAGmaps: Space Filling Visualization of Directed Acyclic Graphs. - Vassilis Tsiaras; Sofia Triantafilou; Ioannis G. Tollis (J. Graph Algorithms Appl., 2009)

Learning Causal Structure from Overlapping Variable Sets. - Sofia Triantafilou; Ioannis Tsamardinos; Ioannis G. Tollis (AISTATS, 2010)

A constraint-based approach to incorporate prior knowledge in causal models. - Giorgos Borboudakis; Sofia Triantafilou; Vincenzo Lagani; Ioannis Tsamardinos (ESANN, 2011)

Learning from Mixture of Experimental Data: A Constraint-Based Approach. - Vincenzo Lagani; Ioannis Tsamardinos; Sofia Triantafilou (SETN, 2012)

Towards Integrative Causal Analysis of Heterogeneous Data Sets and Studies. - Ioannis Tsamardinos; Sofia Triantafilou; Vincenzo Lagani (J. Mach. Learn. Res., 2012)

Learning Neighborhoods of High Confidence in Constraint-Based Causal Discovery. - Sofia Triantafilou; Ioannis Tsamardinos; Anna Roumpelaki (Probabilistic Graphical Models, 2014)

Constraint-based causal discovery from multiple interventions over overlapping variable sets. - Sofia Triantafillou; Ioannis Tsamardinos (J. Mach. Learn. Res., 2015)

Integrative causal analysis of heterogeneous data sets - Sofia Triantafyllou (2015)

SCENERY: A Web-Based Application for Network Reconstruction and Visualization of Cytometry Data. - Giorgos Athineou; Giorgos Papoutsoglou; Sofia Triantafillou; Ioannis Basdekis; Vincenzo Lagani; Ioannis Tsamardinos (PACBB, 2016)

Marginal Causal Consistency in Constraint-based Causal Learning. - Anna Roumpelaki; Giorgos Borboudakis; Sofia Triantafillou; Ioannis Tsamardinos (CFA@UAI, 2016)

Score-based vs Constraint-based Causal Learning in the Presence of Confounders. - Sofia Triantafillou; Ioannis Tsamardinos (CFA@UAI, 2016)

On scoring Maximal Ancestral Graphs with the Max-Min Hill Climbing algorithm. - Konstantinos Tsirlis; Vincenzo Lagani; Sofia Triantafillou; Ioannis Tsamardinos (Int. J. Approx. Reason., 2018)

Rarely-switching linear bandits: optimization of causal effects for the real world. - Benjamin James Lansdell; Sofia Triantafillou; Konrad P. Körding (CoRR, 2019)

Tuning Causal Discovery Algorithms. - Konstantina Biza; Ioannis Tsamardinos; Sofia Triantafillou (PGM, 2020)

Learning Adjustment Sets from Observational and Limited Experimental Data. - Sofia Triantafillou; Gregory F. Cooper (AAAI, 2021)

Preface: The 2021 ACM SIGKDD Workshop on Causal Discovery. - Thuc Duy Le; Jiuyong Li; Gregory F. Cooper; Sofia Triantafyllou; Elias Bareinboim; Huan Liu 001; Negar Kiyavash (CD@KDD, 2021)

The KDD 2021 Workshop on Causal Discovery (CD2021). - Thuc Duy Le; Jiuyong Li; Gregory F. Cooper; Sofia Triantafillou; Elias Bareinboim; Huan Liu 001; Negar Kiyavash (KDD, 2021)

Using Causal Analysis for Conceptual Deep Learning Explanation. - Sumedha Singla; Stephen Wallace; Sofia Triantafillou; Kayhan Batmanghelich (MICCAI (3), 2021)

Causal and interventional Markov boundaries. - Sofia Triantafillou; Fattaneh Jabbari; Gregory F. Cooper (UAI, 2021)

Causal Markov Boundaries. - Sofia Triantafillou; Fattaneh Jabbari; Gregory F. Cooper (CoRR, 2021)

The KDD 2022 Workshop on Causal Discovery (CD2022). - Thuc Duy Le; Lin Liu 003; Emre Kiciman; Sofia Triantafyllou; Huan Liu 001 (KDD, 2022)

Preface: The 2022 ACM SIGKDD Workshop on Causal Discovery. - Thuc Duy Le; Lin Liu 003; Emre Kiciman; Sofia Triantafyllou; Huan Liu 001 (CD@KDD, 2022)

Learning Treatment Effects from Observational and Experimental Data. - Sofia Triantafillou; Fattaneh Jabbari; Gregory F. Cooper (AISTATS, 2023)

Preface: The 2023 ACM SIGKDD Workshop on Causal Discovery, Prediction and Decision. - Thuc Duy Le; Jiuyong Li; Robert Osazuwa Ness; Sofia Triantafillou; Shohei Shimizu; Peng Cui 001; Kun Kuang; Jian Pei 001; Fei Wang 001; Mattia Prosperi (CDPD, 2023)

Augmentation by Counterfactual Explanation -Fixing an Overconfident Classifier. - Sumedha Singla; Nihal Murali; Forough Arabshahi; Sofia Triantafyllou; Kayhan Batmanghelich (WACV, 2023)

ETIA: Towards an Automated Causal Discovery Pipeline. - Konstantina Biza; Antonios Ntroumpogiannis; Sofia Triantafillou; Ioannis Tsamardinos (DS (2), 2024)

Learning Causal Markov Boundaries with Mixed Observational and Experimental Data. - Konstantina Lelova; Gregory F. Cooper; Sofia Triantafillou (PGM, 2024)

Towards Automated Causal Discovery: a case study on 5G telecommunication data. - Konstantina Biza; Antonios Ntroumpogiannis; Sofia Triantafillou; Ioannis Tsamardinos (CoRR, 2024)

Out-of-Sample Tuning for Causal Discovery. - Konstantina Biza; Ioannis Tsamardinos; Sofia Triantafillou (IEEE Trans. Neural Networks Learn. Syst., 2024)

Testing Identifiability and Transportability with Observational and Experimental Data. - Konstantina Lelova; Gregory F. Cooper; Sofia Triantafillou (CoRR, 2025)